Limited contributions of plant pathogens to density‐dependent seedling mortality of mast fruiting Bornean trees

Fungal pathogens are implicated in driving tropical plant diversity by facilitating strong, negative density‐dependent mortality of conspecific seedlings (C‐NDD). Assessment of the role of fungal pathogens in mediating coexistence derives from relatively few tree species and predominantly the Neotropics, limiting our understanding of their role in maintaining hyper‐diversity in many tropical forests. A key question is whether fungal pathogen‐mediated C‐NDD seedling mortality is ubiquitous across diverse plant communities. Using a manipulative shadehouse experiment, we tested the role of fungal pathogens in mediating C‐NDD seedling mortality of eight mast fruiting Bornean trees, typical of the species‐rich forests of South East Asia. We demonstrate species‐specific responses of seedlings to fungicide and density treatments, generating weak negative density‐dependent mortality. Overall seedling mortality was low and likely insufficient to promote overall community diversity. Although conducted in the same way as previous studies, we find little evidence that fungal pathogens play a substantial role in determining patterns of seedling mortality in a SE Asian mast fruiting forest, questioning our understanding of how Janzen‐Connell mechanisms structure the plant communities of this globally important forest type

Distance and density dependence in two native Bornean dipterocarp species

The Janzen–Connell hypothesis proposes that density and distance-dependent mortality generated by specialist natural enemies prevent competitive dominance. Much literature on Janzen–Connell mechanisms comes from the neotropics, and evidence of the role of distance and density-dependence is still relatively sparse. We tested the predictions of the Janzen–Connell hypothesis in a South-East Asian system dominated by mast fruiting species. We hypothesized that seedling survival would decrease with distance and density, seedling growth would increase, and herbivory would decrease, according to the predictions of the Janzen–Connell hypothesis. Experiments were conducted to determine the strength of the Janzen–Connell mechanism by manipulating the density and identity of tree species as a function of the distance from parent trees. Survival of conspecific seedlings was reduced near adult trees of one species, but not another. High densities of seedlings decreased the growth of conspecific seedlings of both species. In both species, herbivory rates decreased with distance in low-density areas. This study indicates that dipterocarp species experienced weak Janzen–Connell effects of distance and density dependence at the growth stage studied. Future studies in this system might focus on earlier life-history stages such as seeds and small seedlings, as well as studying mortality during mast-seeding events

Simulating radiative shocks in nozzle shock tubes

We use the recently developed Center for Radiative Shock Hydrodynamics (CRASH) code to numerically simulate laser-driven radiative shock experiments. These shocks are launched by an ablated beryllium disk and are driven down xenon-filled plastic tubes. The simulations are initialized by the two-dimensional version of the Lagrangian Hyades code which is used to evaluate the laser energy deposition during the first 1.1ns. The later times are calculated with the CRASH code. This code solves for the multi-material hydrodynamics with separate electron and ion temperatures on an Eulerian block-adaptive-mesh and includes a multi-group flux-limited radiation diffusion and electron thermal heat conduction. The goal of the present paper is to demonstrate the capability to simulate radiative shocks of essentially three-dimensional experimental configurations, such as circular and elliptical nozzles. We show that the compound shock structure of the primary and wall shock is captured and verify that the shock properties are consistent with order-of-magnitude estimates. The produced synthetic radiographs can be used for comparison with future nozzle experiments at high-energy-density laser facilities.Comment: submitted to High Energy Density Physic

Path Integrals in Polar Field Variables in QFT

We show how to transform a $d$-dimensional Euclidean path integral in terms of two (Cartesian) fields to a path integral in terms of polar field variables. First we present a conjecture that states how this transformation should be done. Then we show that this conjecture is correct in the case of two toy models. Finally the conjecture will be proven for a general QFT model with two fields

Weldability of polycrystalline aluminides. Final report

When gas-tungsten arc welded, iron aluminides form a coarse fusion zone microstructure which is susceptible to hydrogen cracking. Magnetic arc oscillation and weld pool inoculation were implemented to refine the fusion zone microstructure in iron aluminide alloy FA-129 weldments. Magnetic arc oscillation effectively refined the fusion zone microstructure, and slow strain rate tensile tests showed fine-grained microstructures to be less susceptible to hydrogen cracking. However, magnetic arc oscillation was found to be suitable only for well-controlled fabrication environments. Weld pool inoculation offers a potentially more robust refinement method. Titanium inoculation was also shown to effectively refined the fusion zone microstructure, but weldment properties were not improved using this refinement method. The effect of titanium on the size, shape and distribution of the second phase particles in the fusion zone appears to be the cause of the observed decrease in weldment properties

Canonical Transformations and Path Integral Measures

This paper is a generalization of previous work on the use of classical canonical transformations to evaluate Hamiltonian path integrals for quantum mechanical systems. Relevant aspects of the Hamiltonian path integral and its measure are discussed and used to show that the quantum mechanical version of the classical transformation does not leave the measure of the path integral invariant, instead inducing an anomaly. The relation to operator techniques and ordering problems is discussed, and special attention is paid to incorporation of the initial and final states of the transition element into the boundary conditions of the problem. Classical canonical transformations are developed to render an arbitrary power potential cyclic. The resulting Hamiltonian is analyzed as a quantum system to show its relation to known quantum mechanical results. A perturbative argument is used to suppress ordering related terms in the transformed Hamiltonian in the event that the classical canonical transformation leads to a nonquadratic cyclic Hamiltonian. The associated anomalies are analyzed to yield general methods to evaluate the path integral's prefactor for such systems. The methods are applied to several systems, including linear and quadratic potentials, the velocity-dependent potential, and the time-dependent harmonic oscillator.Comment: 28 pages, LaTe

Current-density functional for disordered systems

The effective action for the current and density is shown to satisfy an evolution equation, the functional generalization of Callan-Symanzik equation. The solution describes the dependence of the one-particle irreducible vertex functions on the strength of the quenched disorder and the annealed Coulomb interaction. The result is non-perturbative, no small parameter is assumed. The a.c. conductivity is obtained by the numerical solution of the evolution equation on finite lattices in the absence of the Coulomb interaction. The static limit is performed and the conductivity is found to be vanishing beyond a certain threshold of the impurity strength.Comment: final version, 28 pages, 17 figures, to appear in Phys. Rev.

A deep learning application to map weed spatial extent from unmanned aerial vehicles imagery

Weed infestation is a global threat to agricultural productivity, leading to low yields and financial losses. Weed detection, based on applying machine learning to imagery collected by Unmanned Aerial Vehicles (UAV) has shown potential in the past; however, validation on large data-sets (e.g., across a wide number of different fields) remains lacking, with few solutions actually made operational. Here, we demonstrate the feasibility of automatically detecting weeds in winter wheat fields based on deep learning methods applied to UAV data at scale. Focusing on black-grass (the most pernicious weed across northwest Europe), we show high performance (i.e., accuracy above 0.9) and highly statistically significant correlation (i.e., ro > 0.75 and p < 0.00001) between imagery-derived local and global weed maps and out-of-bag field survey data, collected by experts over 31 fields (205 hectares) in the UK. We demonstrate how the developed deep learning model can be made available via an easy-to-use docker container, with results accessible through an interactive dashboard. Using this approach, clickable weed maps can be created and deployed rapidly, allowing the user to explore actual model predictions for each field. This shows the potential for this approach to be used operationally and influence agronomic decision-making in the real world

Monitoring lianas from space: using Sentinel-2 imagery to observe liana removal in logged tropical forests

Liana removal – the cutting of over-abundant woody climbing plants (lianas) – has the potential to substantially increase tree growth and biomass accumulation across millions of hectares of degraded tropical forest. Satellite imagery could provide data capable of observing the effect of liana removal on the forest canopy, enabling the large-scale monitoring and validation of liana removal, which remains a key hurdle to its widespread implementation. Using a 320-ha liana removal experiment in Sabah, Malaysian Borneo, we tested whether a time series of Sentinel-2 images could observe the canopy signature of liana removal. Calculating a range of metrics derived from the Normalized Burn Ratio – a vegetation index based on spectral reflectance that differentiates leaf from non-leaf – we quantified satellite-derived canopy disturbance and fragmentation across a range of liana removal intensities and examined how canopy disturbance changed in the 12-months following removal treatments. We find that liana removal significantly increases canopy disturbance and fragmentation metrics one month after removal, with partial removal having a smaller effect than complete removal. The impact of liana removal on the canopy metrics declined over time, with measures of canopy disturbance and fragmentation largely indistinguishable from control forest within 12-months of treatment. Our findings evidence that freely available satellite imagery can be used to efficiently monitor large-scale liana removal applied at a range of intensities and suggest that partial liana removal could significantly reduce canopy disturbance of this restoration method